Table of Contents

• 1. MVC project description
• 2. Setup
• 3. Load the data
• 4. Explore the data
  • 4.1. Muscles by dataset
  • 4.2. Tests by dataset
  • 4.3. Muscles and tests count
  • 4.4. Which test normalizes which muscle
• 5. Tests selection
  • 5.1. Plot the missing values
  • 5.2. Display positions

1. MVC project description

Links

• github repo
• plotly figures

Author: Romain Martinez.

2. Setup

# Common imports
import pandas as pd
# import numpy as np
import scipy.io as sio

# custom functions
import mvc
%load_ext autoreload
%autoreload 2

# Path
from pathlib import Path
PROJECT_PATH = Path('./')
DATA_PATH = PROJECT_PATH / 'data'
MODEL_PATH = PROJECT_PATH / 'model'

# Figures
OFFLINE = True
if OFFLINE:
    import plotly.offline as py
    py.init_notebook_mode(connected=True)
else:
    import plotly.plotly as py
    
import dill as pickle

3. Load the data

df_tidy = pd.read_feather(DATA_PATH / 'df_tidy')
df_tidy_normalized = pd.read_feather(DATA_PATH / 'df_tidy_normalized')
df_wide = pd.read_feather(DATA_PATH / 'df_wide')

with open(MODEL_PATH / 'conf.pkl', 'rb') as h:
    conf = pickle.load(h)

4. Explore the data

4.1. Muscles by dataset

muscle_by_dataset = mvc.plot.count_by_dataset(
    df_tidy,
    values='test',
    index='dataset',
    columns='muscle',
    ylabel=conf['DATASETS'],
    xlabel=conf['MUSCLES'],
    title='Muscles by dataset')
py.iplot(muscle_by_dataset, filename='mvc/muscles_by_dataset')

4.2. Tests by dataset

muscle_by_dataset = mvc.plot.count_by_dataset(
    df_tidy,
    values='muscle',
    index='dataset',
    columns='test',
    ylabel=conf['DATASETS'],
    xtitle='Tests',
    title='Tests by dataset')
py.iplot(muscle_by_dataset, filename='mvc/tests_by_dataset')

4.3. Muscles and tests count

test_count_bar = mvc.plot.count_bar(
    df_tidy, 'test', title='Tests count', xtitle='n', ytitle='Tests')
py.iplot(test_count_bar, filename='mvc/test_count_bar')

muscle_count_bar = mvc.plot.count_bar(
    df_tidy, 'muscle', ylabel=conf['MUSCLES'], title='Muscles count', xtitle='n')
py.iplot(muscle_count_bar, filename='mvc/muscle_count_bar')

4.4. Which test normalizes which muscle

max_by_test = mvc.plot.max_by_test(
    df_tidy_normalized,
    ylabel=conf['MUSCLES'],
    xtitle='Tests',
    title='Which test normalizes which muscle (normalized)')

py.iplot(max_by_test, filename='mvc/max_by_test')

5. Tests selection

5.1. Plot the missing values

nan_count_bar = mvc.plot.count_nan(
    df_wide.iloc[:, df_wide.columns != 'muscle'],
    title='NaN count for each test',
    xtitle='Tests',
    ytitle='NaN count')
py.iplot(nan_count_bar, filename='mvc/nan_count_bar')

5.2. Display positions

IMAGES_PATH = Path('./data/positions_mvc.mat')
positions = sio.loadmat(IMAGES_PATH)['positions']

positions_all = mvc.plot.mvc_positions(
    positions, idx=conf['TESTS'], title='Illustrations of MVIC tests')

py.iplot(positions_all, filename='mvc/positions_all')